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Instructive examples using projects in the Nengo ecosystem

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Recent versions of our CI scripts do static checks on notebooks in addition to .py files, we should do the same here.

``` import nengo_spa as spa import nengo import numpy as np D = 32 sym_keys = {'ONE', 'TWO', 'THREE', 'FOUR'} vocab = spa.Vocabulary(D) vocab.populate(";".join(sym_keys)) with spa.Network() as model: in_state =...

As @xchoo explained it, integrators work by finding fixed points in the representation space. Neural noise means it's possible to escape these fixed points. This escape/drift is easier in higher...

@tcstewar has a bunch of RL and other learning examples in his repo: https://github.com/tcstewar/nengo_learning_examples These examples should be moved into this repo.

Also, this could show how to set a bunch of neurons in direct mode and how that decreases simulation time.

This requires organizing the files under a good root with an `__init__.py`, and writing a `setup.py`. A few things that need to be hashed out before that can be done:...